remote sensing Article Mapping Population Distribution from High Resolution Remotely Sensed Imagery in a Data Poor Setting Sophie Mossoux 1,*, Matthieu Kervyn 2, Hamid Soulé 3 and Frank Canters 4 1 Department of Geography, Cartography and GIS Research Group, Physical Geography, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium 2 Department of Geography, Physical Geography, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium;
[email protected] 3 Centre National de Documentation et de Recherche Scientifique, Observatoire Volcanologique du Karthala, 169 Moroni, Comoros;
[email protected] 4 Department of Geography, Cartography and GIS Research Group, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium;
[email protected] * Correspondence:
[email protected]; Tel.: +32-2-629-33-84 Received: 13 August 2018; Accepted: 3 September 2018; Published: 5 September 2018 Abstract: Accurate mapping of population distribution is essential for policy-making, urban planning, administration, and risk management in hazardous areas. In some countries, however, population data is not collected on a regular basis and is rarely available at a high spatial resolution. In this study, we proposed an approach to estimate the absolute number of inhabitants at the neighborhood level, combining data obtained through field work with high resolution remote sensing. The approach was tested on Ngazidja Island (Union of the Comoros). A detailed survey of neighborhoods at the level of individual dwellings, showed that the average number of inhabitants per dwelling was significantly different between buildings characterized by a different roof type. Firstly, high spatial resolution remotely sensed imagery was used to define the location of individual buildings, and second to determine the roof type for each building, using an object-based classification approach.